The invention relates in general to real-time measuring of voice quality in Voice Over Packet Networks (“VOPN”), and in particular to such measurements by sending voice test signals over Packet networks.
Voice quality can be measured by subjective or by objective methods. International groups carried extensive standardization work on this field. Subjective methods are listening experiments that involve a group of listeners that are presented with voice material. Each individual is asked to rate the speech quality according to a scale from 1 to 5. By averaging the opinion scores a number that reflects the speech quality is obtained. This number is called Mean Opinion Score (MOS) and it is well known for the quality characterization of speech coders. ITU Recommendation P.800 discusses subjective methods and provides with guidelines on how to obtain reliable and reproducible test results. This kind of experiment requires a lot of planning, listening conditions, listening material, selection of an unbiased panel of listeners, etc. Subjective methods are inapplicable to the real time measurement of voice quality.
Objective measurement systems for speech quality measurement use two signals as their input, namely an original signal (reference pattern) and the corresponding output signal after its transition through the network under test. The two signals are compared and an average score reflecting the voice quality is obtained.
The signal processing within objective methods based on the comparison of speech samples can be divided into three major steps: Pre-processing, Psycho-acoustic modeling and Speech Quality estimation model.
The Pre-processing step includes a Delay adjustment to time align properly the two signals and a Loudness adjustment to compensate for differences in power between the reference and transmitted signals.
The Psycho-acoustic model maps the physical signals onto psychophysical representations that match the internal representation of the speech signals. The internal representations make use of psychophysical equivalents of frequency (Bark) and intensity (Compressed Sone).
The Speech Quality estimation model is based on the differences in the internal representation. This difference is used for the calculation of the noise disturbance as a function of time and frequency. This Voice Quality Measurement (VQM) value can be transformed from an objective quality scale to a subjective quality scale. ITU Recommendation P.861 standardizes an objective method called Perceptual Speech Quality Measurement (PSQM). The method is depicted in ITU Recommendation P.861 (1998), “Objective quality measurement of telephone-band and wideband digital codes”. Hollier in U.S. Pat. No. 5,621,854 discloses a second method call PAMS. PSQM and PAMS were originally developed to measure the voice quality delivered by different speech coders and not to test live conditions over a transmission channel. Hollier describes a test apparatus that has access to both ends of a telecom apparatus. Hollier assumes that the whole signal can be stored and later made available for quality measurement and does not disclose how the original test signal and the output signal are aligned to perform the measurement. For loudness adjustment Hollier assumes that the whole signal is available. No mention is made of a network carrying voice by means of data packets and the associated problems like packet loss and jitter.
Several factors affect voice quality in Voice over Packet networks: Delay, Jitter, Packet loss and Speech compression. The Pre-processing steps of Time alignment and Loudness adjustment are simple when the complete signals are available for storage and when the processing can be done off line. These tasks become very complicated if they need to be done in real time under network-degraded conditions. Voice quality measurements are extremely sensitive to any misadjustment during the Pre-processing steps. Misadjustments may be caused by erroneous detection of the beginning of the speech test material and also by missing parts of the speech test signal due to packet loss. They also include effects such as time scale modifications introduced by adaptive jitter buffers embedded in the Voice over Packet equipment. Such problems may severely degrade voice quality measurements.
In order to cope with these problems, measurement methods have been proposed. For example, Agilent introduced in 1999 the Telegra Voice Quality Tester that implements PSQM and PAMS, with a price tag in the range of tens of thousand dollars. The implementation is done using a high end Personal Computer with huge amounts of memory to store the signals and a powerful processor (such as Pentium III, from Intel Corporation) to process the voice signals. Although the solution used is expensive, the measurement is not done in real-time. Test signals are first transmitted from one end of the Tester, recorded at the other end and then processed to obtain a voice quality score.
FIG. 1 shows a typical topology necessary to connect the external test equipment to perform a voice quality measurement according to prior art referred to above. Voice over Internet Protocol (“VOIP”) device 105 and 110 are Voice and Data routers that allow people in two different locations to communicate over an IP network 115. Telephone sets and fax machines 140 and 155 are connected to the VOIP devices for voice and Fax transmission. Computer terminals 130 and 150 are connected for Data transmission. In order to assess the voice quality perceived at both ends, test equipment must be connected to both ends. As the locations are geographically distant the connection presents a challenge. The equipment is connected to the far end via the PSTN 125 (Public Switched Telephone Network) and in this case is not measuring just the degradations introduced by the IP network but also any degradation introduced by the PSTN. A second possibility would be to connect two test equipment systems, one at each end and try to synchronize the measurements.
The prior art system of FIG. 1 is useful when planning and simulating a network under laboratory conditions where all the equipment is at the same location. In an operating network, the creation of observation reference points for measuring voice quality is a difficult task. One of the main problems network administrators face is the distance separation between observation points because tests that require timing synchronization among distant instruments are complicated.